A framework for capturing heterogeneity, heteroskedasticity, non-linearity, reference dependence and design artefacts in value of time research

Abstract

Article:Hess, S orcid.org/0000-0002-3650-2518, Daly, A orcid.org/0000-0001-5319-2745, Dekker, T orcid.org/0000-0003-2313-8419 et al. (2 more authors) (2017) A framework for capturing heterogeneity, heteroskedasticity, non-linearity, reference dependence and design artefacts in value of time research. Transportation Research Part B: Methodological, 96. ReuseThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can't change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. AbstractIn early 2014, the UK Department for Transport (DfT) commissioned the first national value of travel time (VTT) study since the mid-1990s. This paper presents the methodological work undertaken for this study, with important innovations along a number of dimensions, both in terms of survey design and modelling methodology. Our findings show a rich pattern of heterogeneity across the travelling public, in terms of an impact on the VTT by both person and trip characteristics, as well as a major role for a number of characteristics that relate to the specific choices faced in a hypothetical stated choice setting, including reference dependence and non-linearities in sensitivities. We also discuss how these behavioural values were translated into values for use in appraisal, and the challenges faced when doing this on the basis of results obtained with advanced models.1 The project was managed by ARUP, with ITS Leeds (in conjunction with John Bates) being responsible for the survey design, modelling work, and translation of modelled values into appraisal values. Data collection was carried out by Accent. Further information on the study as a whole can be found in the final report (Arup/ITS/Accent, 2015). 2 Other public transport encompassed tram, light rail and underground. 3 In order to mitigate order effects, SP1 (the easiest game) was presented initially, whilst the order of SP2 and SP3 was randomised.

New appraisal values of travel time saving and reliability in Great Britain

“…The present study exploited many of these developments, relating to the error structure of the models, the treatment of reference dependence (size and sign effects) and the incorporation of unobserved preference heterogeneity in valuations. These developments are summarised in the following sub-sections, but interested readers may wish to refer to the fuller technical discussion in the final report of the study (Arup, ITS Leeds and Accent 2015a;Chapter 4) or the companion journal paper (Hess et al 2017).…”

“…Unlike some recent national VTT studies (e.g. Börjesson et al 2012), the log-uniform also avoided the need for censoring of the tails (see the discussion in Hess et al 2017).…”

“…Indeed, some progress towards these ends has already been achieved, with Hess et al (2017) demonstrating the greater robustness of SP3-relative to SP1-towards reference dependence in the SP games. The future availability of data on differing levels of congestion may permit the use of SP3 results in the medium term, though there would still be the need to resolve how model output (in terms of volume/capacity ratios) relates to the levels of congestion presented in the SP, and how to interpolate between the free-flow, light and heavy traffic points.…”

Using Artificial Neural Networks for Recovering the Value-of-Travel-Time Distribution

“…The main reason is that while the travellers' choices are observable (in a real-life setting), their actual trade-offs across alternatives are not -which hampers estimation of the VTT using RP data. More recent VTT studies therefore favour using SC data in combination with sophisticated discrete choice models that account for (some of the) potential artefacts of SC experiments (notably so-called size and sign effects) [4][5][6][7][8].…”

Quantifying errors in travel time and cost by latent variables

“…For instance, there are reasons to expect that travel cost variables have substantial errors, which attenuate the cost parameters in transport models and lead to underestimation of the response to pricing measures in appraisal. Moreover, errors in the time and the cost variables are one major reason for collecting Stated Preference (SP) data for value of time estimation, leading to other problems, such as: reference dependence and gain-loss asymmetry (De Borger and Fosgerau, 2008;Börjesson and Eliasson, 2014;Börjesson and Fosgerau, 2015;Hess et al, 2017).…”